Article Per Year (5 Year)
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This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) International Journal of Informatics and Communication Technology (IJ-ICT) Teknotan: Jurnal Industri Teknologi Pertanian Bulletin of Electrical Engineering and Informatics AGRIEKONOMIKA Dharmakarya : Jurnal Aplikasi Ipteks Untuk Masyarakat Kultivasi Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) SAINS TANAH - Journal of Soil Science and Agroclimatology Syntax Literate: Jurnal Ilmiah Indonesia Jurnal Agrotek Tropika Journal of Tropical Crop Science Indonesian Journal of Electrical Engineering and Computer Science Computer Science and Information Technologies Jurnal Teknik Informatika (JUTIF) Indonesian Journal of Community Services Cel Jurnal Pengabdian Masyarakat Nasional Journal Collabits
Rahmat Budiarto
Department Of Agronomy, Faculty Of Agriculture, Universitas Padjadjaran, Sumedang, 45363, Indonesia
Agriculture, Biological Sciences & Forestry Arts Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Public Health Social Sciences Other

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Clustering man in the middle attack on chain and graph-based blockchain in internet of things network using k-means Nuzulastri, Sari; Stiawan, Deris; Satria, Hadipurnawan; Budiarto, Rahmat
Computer Science and Information Technologies Vol 5, No 2: July 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v5i2.p176-185

Abstract

Network security on internet of things (IoT) devices in the IoT development process may open rooms for hackers and other problems if not properly protected, particularly in the addition of internet connectivity to computing device systems that are interrelated in transferring data automatically over the network. This study implements network detection on IoT network security resembles security systems from man in the middle (MITM) attacks on blockchains. Security systems that exist on blockchains are decentralized and have peer to peer characteristics which are categorized into several parts based on the type of architecture that suits their use cases such as blockchain chain based and graph based. This study uses the principal component analysis (PCA) to extract features from the transaction data processing on the blockchain process and produces 9 features before the k-means algorithm with the elbow technique was used for classifying the types of MITM attacks on IoT networks and comparing the types of blockchain chain-based and graph-based architectures in the form of visualizations as well. Experimental results show 97.16% of normal data and 2.84% of MITM attack data were observed.
Implementation of Banana Cultivation and Post-Harvest Technology in Wanasari Village, Purwakarta Mubarok, Syariful; Budiarto, Rahmat; Rufaidah, Fathi; Mutiara, Pipit; Suminar, Erni; Yani, Yanyan Mochamad
Indonesian Journal of Community Services Cel Vol. 5 No. 1 (2026): Indonesian Journal of Community Services Cel
Publisher : Research and Social Study Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70110/ijcsc.v5i1.131

Abstract

Background: Bananas are among the most important horticultural commodities in Indonesia. In West Java, Purwakarta is a center of banana production. Farmers rely on traditional propagation and production methods, resulting in low yields and productivity. The main problem for banana farmers is the lack of seed availability, where almost no farmer used seed from tissue culture and only 10% of the respondent did not know about post-harvest processing technology.Aims: The aim of this activity is to improve the skills of farmers in the propagation of banana plants by in vitro culture, banana production, and post-harvest technology. This activity took place in Wanasari, Purwakarta City.Methods: The methodology for these activities was to deliver lectures and conduct practice sessions with farmers on banana propagation, production, and postharvest technology. Additionally, we provided them with a banana plant from in vitro culture.Result: The community service activity showed that the farmers were highly interested and enthusiastic about the technology introduced to them with increasing the post-test score of those audiences. The participants' enthusiasm and confidence in implementing banana cultivation and post-harvest techniques demonstrate the effectiveness and practicality of the training methods in supporting banana cultivation. This work is expected to empower farmers to manage their gardens and post-harvest banana handling, thereby contributing to economic resilience and food security.
Optimization of Physalis angulata L. callus induction and salinity-induced antioxidant production Sistyananda, Firstian Naufal; Suminar, Erni; Nuraini, Anne; Kadapi, Muhamad; Murgayanti, Murgayanti; Mubarok, Syariful; Budiarto, Rahmat; Renaldi, Eddy; Kusumiyati, Kusumiyati
Kultivasi Vol 25, No 1 (2026)
Publisher : Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/kultivasi.v25i1.69556

Abstract

Groundcherry (Physalis angulata L.) is a plant with many medicinal potentials due to its rich secondary metabolites such as phenolic and flavonoid. However, conventional agriculture practices are still limited, especially in Indonesia. This study was divided into two stages. The first stage was conducted to determine optimal 6-BAP and 2,4-D combination for callus induction, while the second stage was conducted to determine callus phenolic, flavonoid, and antioxidant response to salinity stress. The first stage was arranged in factorial completely randomized design with two factors: 6-BAP (0, 2, and 4 mg/L) and 2,4-D (0, 0.5, 1, and 1.5 mg/L). The second stage was arranged in simple completely randomized design with different NaCl concentration (0, 25, 50, 75, 100 mM) as treatments. The results showed significant interaction (p < 0.05) between 6-BAP and 2,4-D on callus induction. Combination of 2 mg/L 6-BAP and 1 mg/L 2,4-D showed the highest callus formation percentage (46% increase), callus size (60.12% increase), and fresh weight (179.69% increase), and greener compact callus. Application of NaCl as salinity stress at second stage experiment served as an elicitor to enhance callus antioxidant capacity. Salinity level at 100 mM NaCl showed the most accumulation of phenolic content (17.8% increase), flavonoid content (25.17% increase), and antioxidant activities (6.84% IC50 decrease). This study demonstrates plant growth regulator optimization with salinity stress elicitation integration as an effective strategy to enhance antioxidant production in P. angulata callus, providing a practical approach for controlled secondary metabolite production. 
Machine learning-based anomaly detection for smart home networks under adversarial attack Juli Rejito; Deris Stiawan; Ahmed Alshaflut; Rahmat Budiarto
Computer Science and Information Technologies Vol 5, No 2: July 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v5i2.p122-129

Abstract

As smart home networks become more widespread and complex, they are capable of providing users with a wide range of applications and services. At the same time, the networks are also vulnerable to attack from malicious adversaries who can take advantage of the weaknesses in the network's devices and protocols. Detection of anomalies is an effective way to identify and mitigate these attacks; however, it requires a high degree of accuracy and reliability. This paper proposes an anomaly detection method based on machine learning (ML) that can provide a robust and reliable solution for the detection of anomalies in smart home networks under adversarial attack. The proposed method uses network traffic data of the UNSW-NB15 and IoT-23 datasets to extract relevant features and trains a supervised classifier to differentiate between normal and abnormal behaviors. To assess the performance and reliability of the proposed method, four types of adversarial attack methods: evasion, poisoning, exploration, and exploitation are implemented. The results of extensive experiments demonstrate that the proposed method is highly accurate and reliable in detecting anomalies, as well as being resilient to a variety of types of attacks with average accuracy of 97.5% and recall of 96%.
Detection of android malware with deep learning method using convolutional neural network model Reza Maulana; Deris Stiawan; Rahmat Budiarto
Computer Science and Information Technologies Vol 6, No 1: March 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/csit.v6i1.p68-79

Abstract

Android malware is an application that targets Android devices to steal crucial data, including money or confidential information from Android users. Recent years have seen a surge in research on Android malware, as its types continue to evolve, and cybersecurity requires periodic improvements. This research focuses on detecting Android malware attack patterns using deep learning and convolutional neural network (CNN) models, which classify and detect malware attack patterns on Android devices into two categories: malware and non-malware. This research contributes to understanding how effective the CNN models are by comparing the ratio of data used with several epochs. We effectively use CNN models to detect malware attack patterns. The results show that the deep learning method with the CNN model can manage unstructured data. The research results indicate that the CNN model demonstrates a minimal error rate during evaluation. The comparison of accuracy, precision, recall, F1 Score, and area under the curve (AUC) values demonstrates the recognition of malware attack patterns, reaching an average of 92% accuracy in data testing. This provides a holistic understanding of the model's performance and its practical utility in detecting Android malware.
Chemical properties analysis of liquid and semi-solid bioconversion products from organic waste and their effects on soil fertility and sweet corn yield Sofyan, Emma Trinurani; Sari, Stefina Liana; Rohman, Saefur; Permana, Indra; Budiarto, Rahmat; Ghorbanpour, Mansour; Anindita, Sastrika
SAINS TANAH - Journal of Soil Science and Agroclimatology Vol 22, No 1 (2025): June
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/stjssa.v22i1.95664

Abstract

Food security remains a critical global challenge, particularly as land degradation, driven by excessive use of synthetic fertilizers, continues to threaten soil fertility and crop productivity. This study aimed to evaluate the characteristics of liquid and semi-solid fermented organic waste and their effects on several soil chemical properties and sweet corn yield. The experiment was conducted in a corn field in Pagerwangi Village, West Java, Indonesia. The experiment used a Split-Plot Design with three replications. The main plot was the fermented waste product treatment, which consisted of three levels: no product (A0), liquid product (A1), and semi-solid product (A2). The subplot was the N-P-K dose level, which consisted of four levels: 0 N-P-K (a0), 1/2 N-P-K dose (a1), 3/4 N-P-K dose (a2), and standard N-P-K dose (a3). The research findings indicated that the macro and microelements present in semi-solid products were several times higher compared to liquid ones. Furthermore, the microbial population in semi-solid products exhibited higher density compared to liquid products. Field tests also demonstrated that both liquid product (A1) and semi-solid product (A2) significantly increased total nitrogen, organic-C, and soil pH compared to the control (A0). The highest sweet corn productivity was observed in treatment A2, with a yield increase of 47.62% compared to the control. The research results suggested that the use of fermented organic waste products could enhance soil fertility and sweet corn production.
Restoring subsoil degradation with mixed fertilizer-conditioner: A case study on red chili pepper (Capsicum annuum) cultivation Sari, Stefina Liana; Khuong, Nguyen Quoc; Sofyan, Emma Trinurani; Rohman, Saefur; Budiarto, Rahmat; Solihin, Eso
SAINS TANAH - Journal of Soil Science and Agroclimatology Vol 22, No 2 (2025): December
Publisher : Universitas Sebelas Maret

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20961/stjssa.v22i2.97637

Abstract

The loss of topsoil in high-rainfall regions significantly reduces agricultural productivity, especially in degraded soils. This study investigated the effects of Mixed Fertilizer-Conditioner (MFC) on improving the chemical properties of subsoil cultivated with red chili peppers. A Randomized Block Design (RBD) with 11 treatments on subsoil and one control on normal soil was implemented, with three replications. The treatments included: A= subsoil without fertilizer, B= 0% MFC + full NPK, C= 25% MFC + full NPK, D= 50% MFC + full NPK, E= 75% MFC + full NPK, F= 100% MFC + full NPK, G= 50% MFC + 75% NPK, H= 50% MFC + 50% NPK, I= 50% MFC + 25% NPK, J= 50% MFC without NPK, and K= Full NPK on normal soil. The application of 100% MFC combined with full NPK significantly enhanced subsoil chemical properties. Soil organic carbon increased to 1.32%, pH rose to 6.3, CEC reached 22.1 cmol kg⁻¹, and base saturation improved to 49.4%. Nutrient availability also increased, including total N (1.21%), P (0.132%), K (0.677 cmol kg⁻¹), along with Ca (1362.72 ppm), Mg (311.04 ppm), and S (36.01 ppm). Micronutrients B, Co, and Zn also rose to 4.41 ppm, 18.95 ppm, and 11.97 ppm, respectively. Chili yields in subsoil treated with 50–100% MFC and full NPK exceeded 10 tons ha⁻¹. These results highlight the agronomic potential of MFC for rehabilitating degraded soils and recommend its use as a sustainable strategy to enhance soil fertility in low-fertility or erosion-prone areas, with implications for both farmers and agricultural policymakers.
Co-Authors Abdullakasim, Supatida Adi Hermansyah, Adi Aditya Pradana Ahmad Heryanto, Ahmad Ahmed Alshaflut Al Aufa, Elfa Muhammad Ihsan Ali Firdaus ANDRIA AGUSTA Anindita, Sastrika Anne Nuraini Anni Yuniarti Anto Saputra, Iwan Pahendra Audrey, Berby Febriana Azka Ghafara Putra Agung Bedine Kerim, Bedine Bin Idris, Mohd Yazid Deris Stiawan Dikdik Kurnia Dwi Budi Santoso Dwinanda, Syahvan Rifqi Eddy Renaldi Edi Santosa Efendi, Darda Emma Trinurani Sofyan Envry Artanti Duidahayu Putri Erik Setiawan Ermatita - Erni Suminar Eso Solihin Ezura, Hiroshi Fadlan Atalla Muhammad Fajri, Hauzan Ariq Musyaffa Fakhrurroja, Hanif Farida Farida Farida Fauziah, Rossita Fiky Yulianto Wicaksono Firnando, Rici Firstina Iswari Ghorbanpour, Mansour Giyarto, Gunes Hadipurnawan Satria Haryanto, Yoyon Hauzan Ariq Musyaffa Fajri Hayane Adeline Warganegara, Hayane Adeline Helvi Yanfika Idris, Mohd Yazid Bin Iman Saladin B. Azhar Indah Listiana Indra Permana, Indra Iswari, Firstina Jajang Sauman Hamdani Jatmika, Muhammad O. Juli Rejito Kemahyanto Exaudi Khuong, Nguyen Quoc Komala, Mega Kus Hendarto, Kus Kusumadewi, Vira Kusumiyati Kusumiyati Luciana Djaya, Luciana M. Miftakul Amin Maolana, Adrian Mochamad Arief Soleh Mohamed Shenify Mohd Yazid Idris Mohd Yazid Idris Mohd. Yazid Idris Mugianto, Dwi Rizki Muhamad Kadapi Muhammad Afif Muhammad Rizki Muhammad, Fadlan Atalla Murgayanti Murgayanti Mutiara, Pipit Nisa, Kahirun Noor Istifadah Nursuhud Nursuhud Nuzulastri, Sari Osman, Mohd Azam Pakpahan, Hansel Arie Pertiwi, Hanna Pratita, Dian Galuh Pratomo, Adji Putra Perdana Prasetyo, Aditya Putri, Azizah Tiara Putri, Dina Putri, Envry Artanti Duidahayu Rahma, Siti Auliya Rahmad, Khozaeni Bin Rahmat, Bayu Pradana Nur Ramadani, Selika Fitrian Reza Maulana Rika Meliansyah Roedhy Poerwanto Rofiq, Muhamad Abdul Rohman, Saefur Rossita Fauziah Rufaidah, Fathi Ruminta Ruminta Samsuryadi Samsuryadi Sari, Stefina Liana Sarmayanta Sembiring Semendawai, Jaka Naufal Setiawan, Deris Sidabutar, Alex Onesimus SIska Rasiska, SIska Sistyananda, Firstian Naufal Siti Julaeha, Siti Susanto Susanto Syamsul Arifin, M. Agus Syariful Mubarok Varinto, Irvan Waluyo, Nurmalita Wawan Sutari Wibawa, Rangga Widyastuti, R.A.D. Yanyan Mochamad Yani Yaya Sudarya Triana Yazid Idris, Mohd. Yudho Suprapto, Bhakti Yulianto, Fiky Yusti Yusti, Yusti Zulhipni Reno Saputra Els